Kindly extend your support for these roles,
Strong financial and banking domain experience must need.
Job Title:
Tech Lead / Lead Architect – RAG & Agentic AI
Location: Columbus, OH/ Wilmington, DE – 3 days onsite role
Long Term Project
Client: JPMC
Role Summary:
Lead architecture, design, and delivery of Agentic AI and RAG-based solutions, partnering with customers and internal teams to build scalable, secure, and high-impact AI systems.
Must-Have:
-
Strong experience in
RAG pipelines, embeddings, vector DBs, LLM orchestration, and
prompting techniques.
-
Hands-on expertise in AWS (Lambda, API Gateway, Bedrock, S3, OpenSearch, IAM, VPC, Secrets Manager).
-
Ability to
design end-to-end AI architecture and build PoCs before committing solutions to customers.
-
Deep understanding of
AI guardrails (toxicity, hallucination control), data privacy, and cloud security patterns.
-
Proven ability to lead from the front, mentor teams, and own delivery under tight timelines and high visibility.
-
Strong customer communication skills – ability to explain architecture, trade-offs, and risks clearly.
-
Experience handling model evaluation, observability, performance tuning, and cost optimization in production AI systems.
-
Expertise in API design, microservices integration, and event-driven architectures for AI systems.
Good-to-Have:
-
Experience with
Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel,
etc.).
-
Exposure to marketing domain use cases (campaign optimization, personalization, analytics, insights).
-
Familiarity with
multi-agent orchestration,
tool usage (MCP), and human-in-loop workflows.
✅ Screening Checklist (Quick Evaluation for
Interviews)
Use this to quickly filter candidates:
Technical Fit
-
❑ Can clearly explain a RAG architecture
(data ingestion → embedding → retrieval → generation)
-
❑ Has built or deployed production AI/LLM
solutions (not just POCs)
-
❑ Understands agent lifecycle, orchestration,
and tool integrations
-
❑ Demonstrates AWS architecture + security
(IAM roles, network isolation, secrets)
-
❑ Knows prompt engineering + evaluation
+ guardrails implementation
Architect & Leadership Fit
-
❑ Has led architecture/design discussions
with customers
-
❑ Can drive PoC → production transition
independently
-
❑ Shows ownership mindset (decision-making
without dependency)
-
❑ Can mentor/coach developers and review
designs/code
Communication & Behavioral Fit
-
❑ Explains complex AI topics in simple,
structured way
-
❑ Asks insightful, strategic questions
-
❑ Demonstrates
ability to handle ambiguity and pressure